Recently, many studies on autonomous vehicles are under way. Location recognition and positioning system for cars are one of the very essential parts in unmanned vehicles. These systems are on the basis of GNSS(Global Navigation Satellite System), usi...
Recently, many studies on autonomous vehicles are under way. Location recognition and positioning system for cars are one of the very essential parts in unmanned vehicles. These systems are on the basis of GNSS(Global Navigation Satellite System), using GPS (Global Positioning System)and it calculates location of the receiver using triangulation according to the moment when the satellite signal reaches to the receiver on the surface of the earth by using satellite network moving around the space orbit to measure the position. About seven-meter margin of measurement error occurs, resulting from various error factors. In addition, a margin of error of DGNSS(Differential GNSS) is merely about two meters, compared to GNSS by revising errors on a satellite clock, the ionosphere, the and the track, using Master Station on the ground, but accurate measurement is difficult to make in urban multi-path environment as GNSS is. As part of the improvement, researches are in progress to enhance accuracy of the position, fusing INS, Vision, Radar, Terrestrial Magnetism Sensor, Wi-Fi, etc. INS-GPSis one of the most typical sensor fusion positioning system, having problems with sharp occurrence of measurement errors in accordance with time. Plus, its performance is degraded in GPS interfering spots due to its high dependence on GPS. In short, sensor fusion positioning technique continues to be studied with many unsettled matters.[1-13]
To supplement problems with the current positioning system of vehicles, this paper suggests a positioning technique on the road by analyzing chromaticity coordinate, judging from color temperature of LED street lights and tunnels which are one of infrastructures on the roadway. The positioning technique developed in this paper is expected to be applicable when it is difficult to recognize lanes on account of their poor conditions and in GPS interfering spots by examining LED lights with different color temperatures on the respective roads for positioning locations on the road. Many research bodies are studying on the positioning system and it is considered to improve the performance as the technique covered on this paper applies to the conditions.
This paper consists of five chapters. Chapter 2 describes a chromaticity-related theory of LED lights to help understand the context of the research. Chapter 3 outlines the system structure for measuring chromaticity of LED lights. Chapter 4 gives a description of designing fuzzy controller and the experiment result. Chapter 5 suggests future research direction and the conclusion on positioning on the road using chromaticity of LED lights, based on the experiment result.